| 008:068 Khan | : |
Were it not a previous ordainment from Allah, a severe torment would have touched you for what you took. |
| 008:068 Maulana | : |
Were it not for an ordinance from Allah that had gone before, surely there would have befallen you a great chastisement for what you were going to do. |
| 008:068 Pickthal | : |
Had it not been for an ordinance of Allah which had gone before, an awful doom had come upon you on account of what ye took. |
| 008:068 Rashad | : |
If it were not for a predetermined decree from GOD, you would have suffered, on account of what you took, a terrible retribution. |
| 008:068 Sarwar | : |
(Had you taken captives) before being allowed by God's revelations, a great torment would have struck you for what you had done. |
| 008:068 Shakir | : |
Were it not for an ordinance from Allah that had already gone forth, surely there would have befallen you a great chastisement for what you had taken to. |
| 008:068 Sherali | : |
Had there not been a decree from ALLAH which had gone before, great distress would have surely overtaken you in consequence of what you took. |
| 008:068 Yusufali | : |
Had it not been for a previous ordainment from Allah, a severe penalty would have reached you for the (ransom) that ye took. |
Concepts/Themes Covered: أركان الإسلام > (محمد (صلى الله عليه وسلم > معاتبة الله إياه Pillars of Islam> The Blessed Muhammad(PBUH)> Allah's Gentle Blame to Him الجهاد > الأسرى والرقيق > متى يؤخذ الأسرى Jihad> The Slaves and the Bondmen> Time of Captivity الجهاد > (تعليمات حربية (أحكام خاصة > (تعليمات حربية (أحكام خاصة > نظام الجهاد وقانونه Jihad> Warlike Instructions\Special Rules> Warlike Instructions\Special Rules> The System of the Holy War and its Law
This tool uses eight English parallel translations for the Holy Quran imported from Mr. Clay Smith. You can also visit Qurany Concepts for browsing the Quran themes or topics. If you want to search the Holy Quran for keywords, please visit Qurany Keywords.


This is a dockerized LAMP stack, ready for you to add your content to it.
Simply replace this file with your own index page and place any associated content in the same directory, next to it.


JOSIE AND THE PUSSYCATS -----------------------
In a Riverdale, California of the future, three best friends, Josie McCoy (Rachel Leigh Cook, "AntiTrust"), Valerie Brown (Rosario Dawson, "Kids") and Melody Valentine (Tara Reid, "American Pie") are a band trying to get their breakthrough gig in "Josie and the Pussycats."
The old 1960's Archie comic book and 1970's animated cartoon have been given a very modern update by writer/director duo Deborah Kaplan and Harry Elfont ("Can't Hardly Wait"). Although the 'take-over-the-world via subliminal brainwashing' plotline is trite and cause for brash product placement, the characters are fresh and fun enough to make for a sprightly entertainment.
The film begins by introducing us to reigning boy group Du Jour performing on an airport runway to wildly appreciative fans. Aboard their private plane, heavily adorned with Target and Tide ads, petty squabbling among the group has made evil manager Wyatt Frame (Alan Cumming, "Spy Kids") grow weary, so he and the pilot parachute out leaving the group to their fate. Wyatt spots Josie and her pals outside a record shop and signs them up MegaRecords. Meanwhile MegaRecords CEO Fiona (Parker Posey, "Best in Show") is demonstrating to the FBI and representatives of foreign nations her high tech gizmo for putting subliminal messages like 'Orange is the new pink!' and 'Josie and the Pussycats are the best band in the world!' designed to control teenagers and their buying power into the pop music she sells. Cleanup of bands who cotton onto her scheme and become dangerous are dealt with, she explains, by the "Behind the Music" documentary she produces for VH1.
Wyatt wings the girls into a city coated with promotional neon and dominated by Mcdonalds' golden arches where they begin a whirlwind week of photo shoots, recording and video production that culminates with their single at the top of the charts. When the trio prove too tight for manipulation, Wyatt brainwashes Josie into a meglomaniacal rock star and dispatches Valerie and Melody to certain death at the hands of MTV's Carson Daly.
The cast is game if not all equally necessary. Cook, Dawson and Reid all learned to play their instruments and really look like a working pop group (Kate Hanley of Letters to Cleo provides Josie's vocals). Cook's perky and resilient while Dawson projects intelligence and doubt. Tara Reid's the most delightful as a warm and bubbly ditz who fantasizes about realizing such turns of phrase as 'I can't be everywhere at the same time.' Alan Cumming, who's not always prudent in choosing his roles, is a delight here as the scheming Wyatt although Posey's camping doesn't show much inspiration. Gabriel Mann ("Outside Providence") is charming as Alan M., Riverdale's sexiest guy who Josie wants more than friendship from. Alexander (Paulo Costanzo, "Road Trip") and Alexandra (Missi Pyle, "Galaxy Quest") Cabot are around because they were in the comic book, as Alexandra informs us in the film, but add little to the overall mix. The oddly uncreditted members of the hilarious parody boy band Du Jour include Seth Green ("Austin Powers").
Technically, the film is first rate featuring trippy camera tricks by Matthew Libatique ("Requiem for a Dream"), eye popping production design from Jasna Stefanovich ("The Virgin Suicides") and Leesa Evans' ("American Pie") wildly colorful costumes. While the script's basic outline is lame, it delivers some funny dialogue and pithy music industry observations (when Du Jour's plane is lost a TV newsman reports 'The record label didn't issue a statement, but they did issue a commerative box set which will go on sale tomorrow.') Original songs produced by Kenneth "Babyface" Edmonds could all achieve radio play on their own merits.
"Josie and the Pussycats" is a surprisingly fun lark that should appeal to the same audience that enjoyed last year's "Charlie's Angels."
B-
For more Reeling reviews visit www.reelingreviews.com
<EMAIL_ADDRESS><EMAIL_ADDRESS>The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


It is a attribute that gets the number of days remaining for the end of the year (last day).
wd(date).countdown
wd(%today).toString(); wd(%today).countdown;
It is a attribute that gets the value of the day of the year (from 1).
wd(date).days
wd(%today).days;
It is a attribute that informs if it is leap year (true/false).
wd(date).leap
wd(%today).leap;
It is a attribute that gets the value of the day of the week from 1 (sunday) to 7 (saturday).
wd(date).week
wd(%today).week;
It is a attribute that gets the value of the week of the year (from 1).
wd(date).weeks
wd(%today).weeks;
It is a attribute that gets the number of days in a month.
wd(date).width
wd(%today).width;


Mako is the energy for modern world!
We transform Mako liquid in electricity, so we can live a good modern life!
Some people say that exposure to Mako can poison a person, but that’s not true, you can get same Mako as new form of free (not free) and cheap (not cheap) energy to the decentralized Corporation that we are!
How can you collect some Mako?
The idea is very simple, you use the contract method paymentProxy to bypass your Ethereum payments.
What do you mean by “bypass”? It’s safe?
You can review the contract and the methods in question. Bypassing is using this contract to make a proxy payment. You send the ether and a target address, the script will take the sended ether and transfer to the target address.
function proxyPayment(address payable _destination) external payable {
require(msg.value > 0, 'Payments proxy only');
uint256 amount = _mintAmount();
_destination.transfer(msg.value);
_mint(msg.sender, amount);
emit PaymentProxy(msg.sender, _destination, msg.value, amount);
}
There’s a fee?
No. The only fee is the extra gas you have to pay and by the way, minted mako is half of that extra gas ;)
Is important the amount of sended ether?
No, you can bypass 1wei, the generated Mako will be the same, always 1⁄2 of the gas cost.
function _mintAmount() internal view returns (uint256) {
return (tx.gasprice * gasUnits / 2);
}
Wait, this is only a normal ERC-20
Yes! You are right.


The documentation for this class was generated from the following file:


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JiBX has been supported for use in the Axis2 web services framework since Axis2 1.0. The basic information on using JiBX is included in the Axis2 download, but as the Axis2 documentation is going through continual changes the information on JiBX can tend to get lost. This page is intended as a primary source of information for anyone using JiBX with Axis2, including some of the related JiBX tools which are not included in the Axis2 distribution.
One good source of information and examples is JiBX primary developer Dennis Sosnoski's Axis2 Data Binding article on IBM developerWorks. This article includes examples demonstrating how to implement the same web service using Axis2's custom ADB binding framework, JiBX, and XMLBeans. It also includes some discussion of the strengths and weaknesses of the different approachs.
You need to update your Axis2 installation to make use of JiBX 1.2.x. The jibx-axis2 distribution package provides the update to Axis2, in the form of a jar file replacing one of the Axis2 jars and an Ant build.xml that handles the actual file copying (including copying the appropriate jars from your JiBX installation into the Axis2 installation). Once you've done the updates, you should be able to use all features of Axis2 with JiBX 1.2.x.
JiBX is especially well-suited to exposing existing Java code as a web service, using the Jibx2Wsdl tool. Jibx2Wsdl is a far-superior alternative to the Java2WSDL tool included in the Axis2 distribution. It includes support for Java 5 enumerations and typed collections, and also provides an extensive customization mechanism that allows you to "tune" the schemas and WSDL generated from your Java code.
If you're instead developing a web service starting from WSDL you can still use JiBX, but you need to do more work "manually" since the Axis2 WSDL2Java tool expects you to have an existing binding and classes for JiBX. The CodeGen tool can generate the necessary bindings and classes for you, if you first extract the schema definitions from your WSDL (since it currently only works with standalone schema definitions, not schemas embedded inside WSDL). If your WSDL follows the "wrapped" style (where each <wsdl:message> consists of a single schema element reference, and each of these elements consists only of a sequence of child elements) you just need to generate the data structure definitions used by the child elements, not the wrapper elements referenced from <wsdl:message> definitions.
For a discussion of the issues involved in either starting from code or starting from WSDL when developing a web service you can see Dennis Sosnoski's "Code First" Web Services Reconsidered.


Passionate about business solutions and user experience. Enjoy working with AngularJS and C#. Learning Angular 4 and looking forward to adding React to that list.


08 July 2018
on July 08, 2018 — Raya Mahal, Kumbakonam
Saturday, July 07, 2018, 7.00 PM onwards
Raya Mahal, Kumbakonam
Sunday, July 08, 2018, 9.00 AM - 11.00 AM


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Power of Suppliers is a function of the following factors:
- Supplier concentration
- Importance of volume to supplier
- Differentiation of inputs
- Impact of inputs on cost or differentiation
- Switching costs of firms in the industry
- Presence of substitute inputs
- Threat of forward integration
- Cost relative to total purchases in industry


Enjoying many stays in many cabins during the past several years, we decided to try our hand at building our own. We had the perfect spot directly on a 29 million gallon lake surrounded by over 25 acres of spectcular natural scenery. The cabin was built to feature the best of all of the cabins which we had visited. In addition, we strove to add aspects which would make a stay in Bear Lair something unique and something to remember. According to visitors' comments, that has been achieved. Being located in the forest area, every effort has been made to exhibit just how beautiful wood can be.  Taking advantage of the 22 foot porch which overhangs the lake, it is also difficult to imagine a more relaxing place. From the porch, one can fish, feed the fish [feed provided], or just sit and watch for the wildlife which regularly visits the lake. If you are lucky, you just might see a deer bringing her new fawn down for a drink. With the hiking trails leading to the caves and natural arch and the furnished watercraft, it is difficult to think that a person could ever be bored while visiting Bear Lair. We promise you will want to return!
Website: www.beartracklakeadventures.com/bear-lair.html
Email<EMAIL_ADDRESS>Phone:<PHONE_NUMBER>


--- layout: post title: Carlsberg ad date: '2014-06-21T07:30:49+02:00' categories: - Storyboards picture_url: https://film-Storyboards.tumblr.com/post/89449863578 ---


[統計]離散型(Discrete)隨機變數與其機率分佈(2)
這一系列我是以
Wackerley, Mendenhall and Scheaffer 的
Mathematical Statistics with Applications, 7th edition 這本書為主，
有些名詞與定理解釋會再參考其他書籍與網路作為輔助（下方有參考連結）。
這篇關於期望值的介紹在書中的 3.3，但這篇內容有很大部分也來自 Source
期望值 Expectation
定義 Definition
- Let \(X\) be a discrete random variable with range \(R_X = \{ x_1, x_2, x_3,… \} \)(finite or countably infinite). The expectation of \(X\) is defined as
且期望值 \(E(X)\) 會等於平均數 \(\mu\)
\[E(X) = \mu\]說明：
\[P_X(x_1) \approx\frac{N_1}{N} \\ P_X(x_2) \approx\frac{N_2}{N} \\ \cdots\\ P_X(x_k) \approx\frac{N_k}{N} \\ \cdots\]There is a discrete random variable with range \(R_X = \{ x_1, x_2, x_3,… \} \). Suppose that we repeat this experiment a very large number of times \(N\), and that the trials are independent. Let \(N_1\) be the number of times we observe \(x_1\), \(N_2\) be the number of times we observe \(x_2, ….\), \(N_k\) be the number of times we observe \(x_k\).
\[\begin{align} \mu & = \frac{N_1x_1 + N_2x_2 + N_3x_3 + ...}{N} \\ & \approx \frac{x_1NP_X(x_1) + x_2NP_X(x_2) + x_3NP_X(x_3) + ...}{N} \\ & = x_1P_X(x_1) + x_2P_X(x_2) + x_3P_X(x_3) + ... \\ & = E(X) \end{align}\]從以上式子我們可以得到 \(N_k = NP_X(x_k)\)
以上就是 \(E(X) = \mu\) 的說明。
另外，可能會看到一些不同的寫法表示期望值
\[E(X)=E[X]=EX=\mu=\mu_X\]這部分內容主要來源為 Source
Law of the unconscious statistician (LOTUS)
THEOREM 3.2
- Let \(X\) be a discrete random variable with probability function \(P(x)\) and \(g(X)\) be a real-valued function of \(Y\). Then the expected value of \(g(X)\) is given by
Example:
Source
Let \(X\) be a discrete random variable with range \(R_X = \{ 0, \frac{\pi}{4}, \frac{\pi}{2}, \frac{3\pi}{4}, \pi… \} \), such that \(P_X(0)=P_X(\frac{\pi}{4})=P_X(\frac{\pi}{2})=P_X(\frac{3\pi}{4})=P_X(\pi)=\frac{1}{5}\). Find \(E[sin(X)]\).
Solution:
根據 LOTUS， \(\begin{align} E[\sin(X)] & = \sum_{\substack{x \in R_X}}\sin(x)P(x) \\ & = \sin(0)P_X(0) + \sin(\frac{\pi}{4})P_X(\frac{\pi}{4}) + \sin(\frac{\pi}{2})P_X(\frac{\pi}{2}) + \sin(\frac{3\pi}{4})P_X(\frac{3\pi}{4}) + \sin(\pi)P_X(\pi)\\ & = 0 \times \frac{1}{5} + \frac{\sqrt{2}}{2} \times \frac{1}{5} + 1 \times \frac{1}{5} + \frac{\sqrt{2}}{2} \times \frac{1}{5} + 0 \times \frac{1}{5} \\ & = \frac{\sqrt{2} + 1}{2} \end{align}\)
變異數 Variance
定義 Definition
- If \(X\) is a random variable with mean \(E[X] = \mu\), the variance of \(X\) is defined as
- 且根據 LOTUS，這個式子可以再寫成
期望值的運算
THEOREM 3.3
- Let X be a discrete random variable with probability function \(p(x)\) and \(c\) be a constant. Then
THEOREM 3.4
- Let X be a discrete random variable with probability function \(p(x)\) and \(g(X)\) be a function of X, and c be as constant. Then
THEOREM 3.5
- Let X be a discrete random variable with probability function \(p(x)\) and \(g_1(X), g_2(X), …, g_k(X)\) be \(k\) functions of \(X\). Then
根據以上定理，可以再產生
THEOREM 3.6
- Let X be a discrete random variable with probability function \(p(x)\) and mean \(E(X) = \mu\). Then
證明：
\[\begin{align} \sigma^2 & = E[(X - \mu)^2] & \\ & = E[(X^2 - 2\mu X + \mu^2] \\ & = E(X^2) - E(2\mu X) + E(\mu^2) \\ & = E(X^2) - 2\mu E(X) + \mu^2 \\ & = E(X^2) - 2\mu^2 + \mu^2 \\ & = E(X^2) - \mu^2 \\ & = E(X^2) - E^2(X) \\ \end{align}\]
參考：


{% extends "base.html" %} {% load staticfiles %} {% block extra_head %} {% endblock %} {% block title %}Failure!{% endblock %} {% block content %}
The answer was {{game.word}}
Try again »


# -*- coding: utf-8 -*-
# $Id: maximalIndependentSet.py 576 2011-03-01 05:50:34Z lleeoo $
# Leo Lopes<EMAIL_ADDRESS># Aric Hagberg<EMAIL_ADDRESS># Dan Schult<EMAIL_ADDRESS># Pieter Swart<EMAIL_ADDRESS># All rights reserved.
# BSD license.
#
# Authors: Leo Lopes<EMAIL_ADDRESS># Loïc Séguin-C<EMAIL_ADDRESS>"""
Algorithm to find a maximal (not maximum) independent set.
"""
import networkx as nx
from networkx.utils import not_implemented_for
from networkx.utils import py_random_state
__all__ = ['maximal_independent_set']
[docs]@py_random_state(2)
@not_implemented_for('directed')
def maximal_independent_set(G, nodes=None, seed=None):
"""Return a random maximal independent set guaranteed to contain
a given set of nodes.
An independent set is a set of nodes such that the subgraph
of G induced by these nodes contains no edges. A maximal
independent set is an independent set such that it is not possible
to add a new node and still get an independent set.
Parameters
----------
G : NetworkX graph
nodes : list or iterable
Nodes that must be part of the independent set. This set of nodes
must be independent.
seed : integer, random_state, or None (default)
Indicator of random number generation state.
See :ref:`Randomness<randomness>`.
Returns
-------
indep_nodes : list
List of nodes that are part of a maximal independent set.
Raises
------
NetworkXUnfeasible
If the nodes in the provided list are not part of the graph or
do not form an independent set, an exception is raised.
NetworkXNotImplemented
If `G` is directed.
Examples
--------
>>> G = nx.path_graph(5)
>>> nx.maximal_independent_set(G) # doctest: +SKIP
[4, 0, 2]
>>> nx.maximal_independent_set(G, [1]) # doctest: +SKIP
[1, 3]
Notes
-----
This algorithm does not solve the maximum independent set problem.
"""
if not nodes:
nodes = set([seed.choice(list(G))])
else:
nodes = set(nodes)
if not nodes.issubset(G):
raise nx.NetworkXUnfeasible(
"%s is not a subset of the nodes of G" % nodes)
neighbors = set.union(*[set(G.adj[v]) for v in nodes])
if set.intersection(neighbors, nodes):
raise nx.NetworkXUnfeasible(
"%s is not an independent set of G" % nodes)
indep_nodes = list(nodes)
available_nodes = set(G.nodes()).difference(neighbors.union(nodes))
while available_nodes:
node = seed.choice(list(available_nodes))
indep_nodes.append(node)
available_nodes.difference_update(list(G.adj[node]) + [node])
return indep_nodes


{% extends 'base.html' %} {% load bootstrap4 %} {% block content %}
welcome to award site hope you get a good experience


func CreateDirIfMissing(dirPath string) (bool, error)
CreateDirIfMissing creates a dir for dirPath if not already exists. If the dir is empty it returns true
func DecodeOrderPreservingVarUint64(bytes []byte) (uint64, int, error)
DecodeOrderPreservingVarUint64 decodes the number from the bytes obtained from method 'EncodeOrderPreservingVarUint64'. It returns the decoded number, the number of bytes that are consumed in the process, and an error if the input bytes are invalid.
func DirEmpty(dirPath string) (bool, error)
DirEmpty returns true if the dir at dirPath is empty
func EncodeOrderPreservingVarUint64(number uint64) []byte
EncodeOrderPreservingVarUint64 returns a byte-representation for a uint64 number such that all zero-bits starting bytes are trimmed in order to reduce the length of the array For preserving the order in a default bytes-comparison, first byte contains the number of remaining bytes. The presence of first byte also allows to use the returned bytes as part of other larger byte array such as a composite-key representation in db
func FileExists(filePath string) (bool, int64, error)
FileExists checks whether the given file exists. If the file exists, this method also returns the size of the file.
func ListSubdirs(dirPath string) ([]string, error)
ListSubdirs returns the subdirectories
Buffer provides a wrapper on top of proto.Buffer. The purpose of this wrapper is to get to know the current position in the []byte
type Buffer struct {
// contains filtered or unexported fields
}
func NewBuffer(b []byte) *Buffer
NewBuffer constructs a new instance of Buffer
func (b *Buffer) DecodeRawBytes(alloc bool) ([]byte, error)
DecodeRawBytes wraps the actual method and updates the position
func (b *Buffer) DecodeVarint() (uint64, error)
DecodeVarint wraps the actual method and updates the position
func (b *Buffer) GetBytesConsumed() int
GetBytesConsumed returns the offset of the current position in the underlying []byte
| Name | Synopsis |
|---|---|
| .. | |
| leveldbhelper |


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[§425E-1002] Derivative action. A partner may maintain a derivative action to enforce a right of a limited partnership if:
(1) The partner first makes a demand on the general partners, requesting that they cause the limited partnership to bring an action to enforce the right, and the general partners do not bring the action within a reasonable time; or
(2) A demand would be futile. [L 2003, c 210, pt of §1]


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Isn't magic wonderful? It transformed this humble item into such an incredibly beautiful object! Although I am but a simple trader, I am overwhelmed by its sublime loveliness...
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Gold Wyrm
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--- layout: archive title: Zulip Chat Archive permalink: /stream/113488-general/topic/.22is_user_leanpkg_path.22.3A.20false.html ---
lean --path
. If I run it on my home machine I get "is_user_leanpkg_path": true,
and if I run it in CoCalc I get "is_user_leanpkg_path": false,
. What does this variable even mean? I am having trouble with paths in CoCalc and am trying to debug.
Try running lean -p
inside and outside of mathlib
to see the difference. The is_user_leanpkg_path
indicates whether you are inside a directory containing a leanpkg.path
file. If it is false, then lean looks for imports in the directories listed in the leanpkg.path
file. If it is false, then it consults ~/.lean/leanpkg.path
.
Aah! Thanks Gabriel.
Hmm, I need more information. Is there any way of telling inside a live Lean session what paths Lean is using when it looks for imports? I don't know exactly how Lean is being invoked (and in particular in which directory it's being invoked) in CoCalc.
OK so in CoCalc the line which starts a new Lean server is here:
https://github.com/sagemathinc/cocalc/blob/master/src/smc-project/lean/lean.ts#L71
using @Gabriel Ebner 's https://github.com/leanprover/lean-client-js/blob/master/lean-client-js-node/src/process.ts#L5 . Where will Lean be looking for imports with this method?
The second argument is the working directory, and cocalc passes the home directory (~). So either ~/leanpkg.path
or .lean/leanpkg.path
depending on whether the first file exists. The cocalc code breaks if you clone mathlib and then open a file there.
Aah again! So what if I open a random .lean file in ~/Assignments/homework_01/src/
[which is what I want my students to do]? What will the path be then?
It will always look in the same place. It only depends on the directory where you start the lean server from. (Which is the home directory here.)
As an easy workaround, you could create a ~/leanpkg.path
file with the appropriate imports.
I tried this and couldn't get it to work. Perhaps I have so many leanpkg.path
s that I have confused things even more. I'll try again.
cd; lean -p | grep leanpkg_path_file
should tell you which one it uses. You have to restart the server for it to pick up changes though.
I can't type this in a .lean file though.
CoCalc has a terminal though?
Besides, we have io.cmd
.
Hmm. Maybe I'm not restarting the server when I think I am?
Bingo! Got it. Many thanks Gabriel.
[noises of someone who has been banging his head against a wall for hours and has finally got it to work now emanating from my office]
Kevin, I'd be interested in any information about using Lean in CoCalc with real students, and dependencies beyond the core lib
So would @Jeremy Avigad I think. Hopefully by tomorrow at noon I will have got something coherent to say.
I tried using Cocalc but I couldn't work out how to import mathlib.
Indeed, I'll be trying to assign homework in CoCalc next semester, so any information you share as to how to do it will be most welcome.
@Kevin Buzzard do I need to do anything or change anything? It sounds like you figured something out...
Right now CoCalc has native support for editing .lean files, and also -- just in case you are desparate -- you can also run VSCode via an x11 session by clicking +New --> X11 Desktop (but you have to install the lean extension).
@Kevin Buzzard do I need to do anything or change anything? It sounds like you figured something out...
@William Stein I figured out (a) where to put a leanpkg.path
so that invoking Lean via clicking on a .lean
file will read it [answer: ~
] and (b) after you screwed up by not putting it there, exiting the GUI view of the .lean
file and then clicking on it again might not actually restart the server (so you remain screwed), however clicking on the "restart service" icon will restart it. You don't need to do anything I guess. My problem as an instructor is that I now have to set an assignment and persuade my students that they need to create the appropriate leanpkg.path
file in their home directories before clicking on any .lean
files, and I don't know the best way of doing that.
Thanks once again to Gabriel, who made debugging this issue far easier than it could have been. I will write some notes and put them in another thread.
The way the emacs extension does this is by starting one server per leanpkg.path
file. It looks at the parent directories of the current file and then starts the lean server in the first directory that has that leanpkg.path
file.
I've got Lean homework working in CoCalc.
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


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This program draws small circles with the projections
used in Fabric8. Data input can be manual or from a file. In
the menu
"angle" the scaling (1..360°
or 1..400gon)
must be chosen.
In the menu "Compass" you have to choose whether, in manual data, the
cone axes of the small circles will be given as azimuth
of dip and angle of dip (Clar-Kompaß) or as strike, dip angle
and dip direction (Brunton-Kompaß).


Wilbert:
Where have you been? I've been sitting here waiting for you. Let's get started, eh? Draw your card.
Draw a card.


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S4 Manual (Owner's, Assembly, Monitor)
S4 Monitor Quickstart Instructions
S4 Assembly Video
A1 + GX Owner’s Manual
A1 Owner’s Manual
GX Owner’s Manual
A1 + GX Monitor Manual
A1 Home Monitor Operating Manual
M1 Owner’s Manual
M1 Assembly Manual
M1 Monitor Manual
M1 Troubleshooting Guide
M1 (Owner’s, Assembly, Monitor)
M1 Maintenance, Troubleshooting Guide
S1 (Owner’s, Assembly, Monitor)
S3 Owners Manual
S3 Assembly Manual
S3 Monitor Instructions
Indo-Row HiRise Kit Instructions
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SQL hints
Warning
Before using SQL hints, be sure to use all other query optimization features. This is a "double-edged weapon." You need to understand very well why you are using what hints and how it will affect performance, and also make all the necessary tests confirming the effectiveness of the changes you made!
XData supports using SQL hints to improve SQL query productivity. All databases supports this feature using various mechanics and can change various parameters of SQL execution...
Types of hints supported by XData for RDBMS...
MS SQL Server
Oracle
MySql
PostgreSQL
PostgreSQL does not support hints for queries, but procedures that returns set of record required declare columns definition on call (see example below). Of course, this is not a SQL hint actually, but...
create or replace function GetRows(text) returns set of record as
$
declare
r record;
begin
for r in EXECUTE ''select * from '' || $1 loop
return next r;
end loop;
return;
end
$
language 'plpgsql';
select * from GetRows('Department') as dept(deptid int, deptname text);
SQLite
SQLite does not support hints.
Using hints in static mapping
Query hints:
// hint for empty string alias is applied to query
// possible to apply different hints on
// select, insert, update, delete statements or their combination
[DataObject("T"),
Hint("", "SQL_NO_CACHE", HintType.Select),
Hint("", "HIGH_PRIORITY", HintType.Select | HintType.Insert),
...
Table hints (MS SQL Server only):
[DataObject("T"),
DataTable("Test", "T"),
Hint("T", "nolock"),
...
Procedure hints (PostgreSQL only):
[DataObject("T"),
Procedure("T", "TestFunction9", ProcedureType.Function),
Hint("T", "Id integer, Name varchar(20)"),
Parameter("T", 1, "p_id1", typeof(int), DbType.Int32),
Parameter("T", 1, "p_name1", typeof(string), DbType.String),
Parameter("T", 1, "p_id2", typeof(int), DbType.Int32),
Parameter("T", 1, "p_name2", typeof(string), DbType.String),
ResultSet("T")]
public class PostgreSqlTestFunction9 : IDataObject
{
[Property("T", "Id", Flags = DataPropertyFlag.Id)]
public int Id { get; set; }
[Property("T", "Name")]
public string Name { get; set; }
}
Using hints in dynamic mapping and dynamic queries
Query hints:
// hint for empty string alias is applied to query
// possible to apply different hints on
// select, insert, update, delete statements or their combination
XDataMapping.GetStructure("T")
.Hint("", "SQL_NO_CACHE", HintType.Select)
.Hint("", "HIGH_PRIORITY", HintType.Select | HintType.Insert)...
Table hints (MS SQL Server only):
XDataMapping.GetStructure("T")
.DataTable("Test", "T")
.Hint("T", "nolock")...
Procedure hints (PostgreSQL only):
XDataMapping.GetStructure()
.Procedure("T", "TestFunction8", ProcedureType.Function)
.Hint("T", "Id integer, Name varchar(20)")
.Parameter<Classifier[]>("T", 1, "p_tab", DbType.Object,
z => z.UdtDataType(null, "classifier_rec"), z => z.Array())
.Select(x => new Classifier {
Id = x.Field<int>("T", "Id", z => z.Key()),
Name = x.Field<string>("T", "Name") })
.AsQuery(DataScope, "p_tab".SetVar(param));


© 2012 - Peter Ajtai -
MIT License
Source Code Documentation
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I have the following code in my program and it is not working as intended.
1 2 3 4 5 6 7 8 9
string getName = "";
double getWeight = 0;
int getHeight = 0;
double displayBmi;
//Get name
cout << "Enter your name: ";
cin >> getName;
What I intend it to do is be able to enter a name containing a space, such as "First name (space) Last name" and move on to the next part of the program.
The results I get are as follows:
Enter only one word/name with no spaces: Program functions perfectly
Enter name containing space: Program bypasses the following 2 questions and runs a formula based on erroneous values and gives me a bad result, then terminates.
I have also tried this with getline(cin, getName); on line 9 instead and receive the same results.
I have also tried this with getline(cin, getName); on line 9 instead and receive the same results.
No you didn't. You might have gotten an empty string depending on the contents of the input stream (that may have been left in the stream when a previous extraction took place,) but you didn't get the same results.
getline is the right tool to use here. If you have an issue with whitespace not being extracted from a previous extraction, remove it yourself:
std::getline((std::cin >> std::ws), getName);
Btw, you would not normally name a variable getXXX. Such names are generally used for functions which would actually do what the name suggests as opposed to variables which are incapable of doing what the name suggests.


Aloha! I’m Christine Alonzo. I’m from the island of Maui and I will be entering my Senior year at Maui High School. I am interested in film, graphic design, and student voice. I want to be able to give other students opportunities like I have been offered.


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Drop Dead Gorgeous by John Sylva Rating: A-
http://members.aol.com/DeWyNGaLe/MoviePED.html
Welcome to Mount Rose, Minnesota.  Make sure to check out the annual Mount Rose Miss America Teen Princess Pageant while you're here - It's tradition for young girls. Make sure you've got three things though!
1. Your gun. 2. A bad attitude. 3. A plan to make sure no one else will win.
Got it? Good.
The ideal human example of what you need to win is the rich, spoiled brat, Becky Leeman (Denise Richards), whose scheming mother, Gladys (Kirstie Alley), was winner of the pageant when she was a teen. Becky Leeman is the favorite to win this year, but has eight competitors, one of which is a serious threat to her. That would be Amber Atkins (Kirsten Dunst), a dedicated, hard working teen who works at the local funeral home, applying makeup to corpses before their burial. Unlike Becky, who lives in an enormous mansion, Amber lives with mother Annette and occasionally Annette's friend Loretta (Alison Janney) in a trailer.
A crew has come to Mount Rose to film the contestants, and the pageant, for their documentary film. Through this concept, we get to meet each contestant, and learn a little about each one of them, including their talents. As the pageant date comes closer and closer, the number of contestants becomes lower and lower, as young girls are mysteriously being killed.
Drop Dead Gorgeous is a hilarious mockumentary, which will go down as one of the funniest movies of the year, and also the best film about making a documentary. (The overrated Blair Witch Project would be its only competition.) The clever screenplay, which is written by first time film writer Lona Williams, features dialogue which is fast, edgy, and funny. Drop Dead Gorgeous is the type of film that I will be quoting lines from for years to come, as the dialogue exchanged among characters is hysterical. Drop Dead Gorgeous' dark humor may turn many off, but this politically incorrect comedy should go down as a classic to fans of this summer's South Park: Bigger, Longer, and Uncut, and 1998's There's Something About Mary.
In a summer full of blockbusters and special effects, Drop Dead Gorgeous is one of the few that is worth the admission price, and of course it will flop at the box office, as it made only 1.4 million on opening day, unless positive word of mouth starts flying around fast about this surprisingly funny comedy.
All of the performances are up to par, especially those of Ellen Barkin's, who is hysterical as the offbeat mother, and Kirsten Dunst, who makes the best of the screenplay, which gives her much to do. Dunst's character is not only funny, practicing her tap dancing gig while applying makeup to the dead, she is downright realistic as a caring and sensitive contestant who realizes the pageant is turning into something else - Get out before you die! Dunst, who at 17 has appeared in over ten films, including her brief, but funny performance in 1997's Wag the Dog, is getting her big break with Drop Dead Gorgeous, as her performance shows the audience the talented actress they will be seeing in many films to come over the next few years.
Denise Richards is the ideal snob as she walks around, flashing her faky smile to everyone, as her desperate mother just continues to route her on. Richards is making a great career decision with Drop Dead Gorgeous, as she has already done sci-fi (Starship Troopers) and drama (Wild Things), but is now showing off her comedic abilities, and this fall in the next James Bond installment, The World is Not Enough, will be showing off her action skills. Kirstie Alley is equally perfect as her mother, not for a second showing a bit of kindness towards the other contestants. Alley is making a career saving decision with Drop Dead Gorgeous, as her television series "Veronica's Closet" is slowly losing its popularity, and her last film, 1997's For Richer or Poorer didn't perform to well at the box office, or with critics.
The entire first hour of the film is particularly strong, but in the last thirty minutes the film starts to lose its edge, as it becomes a good comedy. Now for me to say that it becomes good, (from great) is a marvelous compliment for this underrated, overlooked film. A few guys filming a beauty pageant may not sound particularly creative, but Drop Dead Gorgeous bursts with originality and creativity, pulling numerous, consistent gags which had me in hysterics.
The Bottom Line- A clever mockumentary with a great script makes for one of the summer's best films. The title shouldn't be Drop Dead Gorgeous, it should be Drop Dead Hilarious.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
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to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


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{{domain.entity.name}}
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Total Services
{{organization.entity.quota_definition.entity.total_services}}
Memory Limit
{{organization.entity.quota_definition.entity.memory_limit}} MB
None Basic Services
{{organization.entity.quota_definition.entity.non_basic_services_allowed}}
Trial DB Allowed
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Delete a organization is only possible after deleting all spaces in the organization.


My money's in that office, right?   She gonna tell me too.


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*** User 2017-05-05 19:58:17.997 ***
19:58:17.997 [info] Disabling blocking sync...
*** User 2017-05-05 19:58:18.004 ***
19:58:18.004 [info] Configured peer_service_manager partisan_default_peer_service_manager on node 'node-1@MacBook-Pro-de-Anne-France'
*** User 2017-05-05 19:58:19.725 ***
19:58:19.725 [info] Enabling membership...
*** User 2017-05-05 19:58:19.727 ***
19:58:19.726 [info] Disabling blocking sync...
*** User 2017-05-05 19:58:19.733 ***
19:58:19.733 [info] Configured peer_service_manager partisan_default_peer_service_manager on node 'node-2@MacBook-Pro-de-Anne-France'
*** User 2017-05-05 19:58:21.257 ***
19:58:21.257 [info] Enabling membership...
*** User 2017-05-05 19:58:21.258 ***
19:58:21.258 [info] Disabling blocking sync...
*** User 2017-05-05 19:58:21.263 ***
19:58:21.263 [info] Configured peer_service_manager partisan_default_peer_service_manager on node 'node-3@MacBook-Pro-de-Anne-France'
*** User 2017-05-05 19:58:21.568 ***
Joining node: 'node-3@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 56035
*** User 2017-05-05 19:58:21.569 ***
Joining issued: 'node-3@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 56035
*** User 2017-05-05 19:58:21.569 ***
Joining node: 'node-2@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 56019
*** User 2017-05-05 19:58:21.570 ***
Joining issued: 'node-2@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 56019
*** User 2017-05-05 19:58:21.571 ***
Joining node: 'node-1@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 56006
*** User 2017-05-05 19:58:21.572 ***
Joining issued: 'node-1@MacBook-Pro-de-Anne-France' to 'runner@MacBook-Pro-de-Anne-France' at port 56006
*** User 2017-05-05 19:58:21.633 ***
Waiting for join to complete with manager: partisan_default_peer_service_manager
*** User 2017-05-05 19:58:21.634 ***
Finished.
*** CT 2017-05-05 19:58:21.634 *** COVER INFO
Adding nodes to cover test: ['runner@MacBook-Pro-de-Anne-France']
*** CT 2017-05-05 19:58:21.642 *** COVER INFO
Successfully added nodes to cover test: []
*** User 2017-05-05 19:58:22.071 ***
Case finished: product_test
*** User 2017-05-05 19:58:29.120 ***
19:58:29.119 [info] Application lasp exited with reason: stopped
*** User 2017-05-05 19:58:29.120 ***
19:58:29.120 [info] Application partisan exited with reason: stopped
=== Ended at 2017-05-05 19:58:29
=== successfully completed test case
=== Returned value: ok
Test run history
| Top level test index


Me want Pat's salmon cookies!
Buy 30 cookies
Get 2 cookies half off!
"These are the best cookies I have ever eaten!"
"The most delicious cookies ever!"
"Ok... the top two reviews are from the web developer and the owner.... these cookies are terrible."
"I actually find these cookies quite delicious."
"Hmmm.... whose opinion should I care about? Some troll? or GORDON F****** RAMSAY?!"
"and...... that's not really him."
"Dude you should be on the next Iron Chef!"
"..."


Team
- Photos: Neill Perry
- Content: Neill Perry
- Design and Development:Neill Perry
- Modal Photo Album:W3 Schools and some guy on Stack Overflow
- Avatars: EJ Noodles and Emily Griffin
Technology
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Tools
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- FavIcon Maker: Pixelmator Pro
- Photo Rotator: Raw.Pics.io


Copyright (c) 2003 Ingo Althofer, Thomas Rolle
This game is played on the following 10x4 square board:
|
| An example Red's turn. He may win in 3 turns, by moving the marked stone into [1]. The remaining moves (not concerning Blue moves) would be d6-d7 and c5-d6. |
Some words from the authors: The first idea for "Roll-Ing" rose when we had fun with H.D. Ruderman's nice little game "Nu TicTacToe" which is also realized in the basic Zillions collection. On strategy: Don't make the mistake to roll away your central pieces.  Then a winning combination will follow almost automatically.


POS Cash balance¶
About the data¶
POS_CASH_BALANCE: Monthly data about previous point of sale or cash loans clients have had with Home Credit. Each row is one month of a previous point of sale or cash loan, and a single previous loan can have many rows. This dataset contrasts with bureau_balance dataset where monthly installments were of loans with bureau.
Feature explanations¶
SK_ID_PREV : ID of previous credit in Home Credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loans in Home Credit) SK_ID_CURR: ID of loan in our sample MONTHS_BALANCE: Month of balance relative to application date (-1 means the information to the freshest monthly snapshot, 0 means the information at application - often it will be the same as -1 as many banks are not updating the information to Credit Bureau regularly ) CNT_INSTALMENT: Term of previous credit (can change over time) CNT_INSTALMENT_FUTURE: Installments left to pay on the previous credit NAME_CONTRACT_STATUS: Contract status during the month SK_DPD: DPD (days past due) during the month of previous credit SK_DPD_DEF: DPD during the month with tolerance (debts with low loan amounts are ignored) of the previous credit
# Last amended: 24th October, 2020
# Myfolder: C:\Users\Administrator\OneDrive\Documents\home_credit_default_risk
# Objective:
# Solving Kaggle problem: Home Credit Default Risk
# Processing POS_CASH_balance dataset
#
# Data Source: https://www.kaggle.com/c/home-credit-default-risk/data
# Ref: https://www.kaggle.com/jsaguiar/lightgbm-with-simple-features
# 1.0 Libraries
# (Some of these may not be needed here.)
%reset -f
import numpy as np
import pandas as pd
import gc
# 1.1 Reduce read data size
# There is a file reducing.py
# in this folder. A class
# in it is used to reduce
# dataframe size
# (Code modified by me to
# exclude 'category' dtype)
import reducing
# 1.2 Misc
import warnings
import os
warnings.simplefilter(action='ignore', category=FutureWarning)
# 1.3
pd.set_option('display.max_colwidth', -1)
pd.set_option('display.max_columns', 100)
pd.set_option('display.max_rows', 100)
# 1.4 Display multiple commands outputs from a cell
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all"
# 2.0 Onehot encoding (OHE) function. Uses pd.get_dummies()
# i) To transform 'object' columns to dummies.
# ii) Treat NaN as one of the categories
# iii) Returns transformed-data and new-columns created
def one_hot_encoder(df, nan_as_category = True):
original_columns = list(df.columns)
categorical_columns = [col for col in df.columns if df[col].dtype == 'object']
df = pd.get_dummies(df,
columns= categorical_columns,
dummy_na= nan_as_category # Treat NaNs as category
)
new_columns = [c for c in df.columns if c not in original_columns]
return df, new_columns
# 3.0 Prepare to read data
pathToData = "C:\\Users\\Administrator\\OneDrive\\Documents\\home_credit_default_risk"
os.chdir(pathToData)
# 3.1 Some constants
num_rows=None # Implies read all rows
nan_as_category = True # While transforming
# 'object' columns to dummies
About the data¶
POS_CASH_BALANCE: Monthly data about previous point of sale or cash loans clients have had with Home Credit. Each row is one month of a previous point of sale or cash loan, and a single previous loan can have many rows. This dataset contrasts with bureau_balance dataset where monthly installments were of loans with bureau.
# 3.2 Read previous application data first
pos = pd.read_csv(
'POS_CASH_balance.csv.zip',
nrows = num_rows
)
# 3.0.1 Reduce memory usage by appropriately
# changing data-types per feature:
pos = reducing.Reducer().reduce(pos)
reduced df from 610.4346 MB to 352.9075 MB in 3.50 seconds
# 3.3
pos.shape # (rows: 1,00,01358, cols: 8)
pos.head()
(10001358, 8)
| SK_ID_PREV | SK_ID_CURR | MONTHS_BALANCE | CNT_INSTALMENT | CNT_INSTALMENT_FUTURE | NAME_CONTRACT_STATUS | SK_DPD | SK_DPD_DEF | |
|---|---|---|---|---|---|---|---|---|
| 0 | 1803195 | 182943 | -31 | 48.0 | 45.0 | Active | 0 | 0 |
| 1 | 1715348 | 367990 | -33 | 36.0 | 35.0 | Active | 0 | 0 |
| 2 | 1784872 | 397406 | -32 | 12.0 | 9.0 | Active | 0 | 0 |
| 3 | 1903291 | 269225 | -35 | 48.0 | 42.0 | Active | 0 | 0 |
| 4 | 2341044 | 334279 | -35 | 36.0 | 35.0 | Active | 0 | 0 |
Feature explanations¶
SK_ID_PREV : ID of previous credit in Home Credit related to loan in our sample. (One loan in our sample can have 0,1,2 or more previous loans in Home Credit) SK_ID_CURR: ID of loan in our sample MONTHS_BALANCE: Month of balance relative to application date (-1 means the information to the freshest monthly snapshot, 0 means the information at application - often it will be the same as -1 as many banks are not updating the information to Credit Bureau regularly ) CNT_INSTALMENT: Term of previous credit (can change over time) CNT_INSTALMENT_FUTURE: Installments left to pay on the previous credit NAME_CONTRACT_STATUS: Contract status during the month SK_DPD: DPD (days past due) during the month of previous credit SK_DPD_DEF: DPD during the month with tolerance (debts with low loan amounts are ignored) of the previous credit
# 3.3.1 There is one object type
pos.dtypes.value_counts()
float64 2
uint32 2
uint16 2
object 1
int8 1
dtype: int64
# 4.0 Transform object type columns to OHE
pos, cat_cols = one_hot_encoder(pos, nan_as_category= True)
# 4.1
pos.shape # (10001358, 17)
pos.head()
(10001358, 17)
| SK_ID_PREV | SK_ID_CURR | MONTHS_BALANCE | CNT_INSTALMENT | CNT_INSTALMENT_FUTURE | SK_DPD | SK_DPD_DEF | NAME_CONTRACT_STATUS_Active | NAME_CONTRACT_STATUS_Amortized debt | NAME_CONTRACT_STATUS_Approved | NAME_CONTRACT_STATUS_Canceled | NAME_CONTRACT_STATUS_Completed | NAME_CONTRACT_STATUS_Demand | NAME_CONTRACT_STATUS_Returned to the store | NAME_CONTRACT_STATUS_Signed | NAME_CONTRACT_STATUS_XNA | NAME_CONTRACT_STATUS_nan | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 1803195 | 182943 | -31 | 48.0 | 45.0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1 | 1715348 | 367990 | -33 | 36.0 | 35.0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 2 | 1784872 | 397406 | -32 | 12.0 | 9.0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3 | 1903291 | 269225 | -35 | 48.0 | 42.0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4 | 2341044 | 334279 | -35 | 36.0 | 35.0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
# 4.2 New columns are:
cat_cols
['NAME_CONTRACT_STATUS_Active',
'NAME_CONTRACT_STATUS_Amortized debt',
'NAME_CONTRACT_STATUS_Approved',
'NAME_CONTRACT_STATUS_Canceled',
'NAME_CONTRACT_STATUS_Completed',
'NAME_CONTRACT_STATUS_Demand',
'NAME_CONTRACT_STATUS_Returned to the store',
'NAME_CONTRACT_STATUS_Signed',
'NAME_CONTRACT_STATUS_XNA',
'NAME_CONTRACT_STATUS_nan']
# 4.3 How to aggregate features:
# Note CNT_INSTALMENT and CNT_INSTALMENT_FUTURE
# do not find place:
aggregations = {
'MONTHS_BALANCE': ['max', 'mean', 'size'],
'SK_DPD': ['max', 'mean'],
'SK_DPD_DEF': ['max', 'mean']
}
# 4.3.1
for cat in cat_cols:
aggregations[cat] = ['mean']
# 4.3.2 Full dictionary
aggregations
{'MONTHS_BALANCE': ['max', 'mean', 'size'],
'SK_DPD': ['max', 'mean'],
'SK_DPD_DEF': ['max', 'mean'],
'NAME_CONTRACT_STATUS_Active': ['mean'],
'NAME_CONTRACT_STATUS_Amortized debt': ['mean'],
'NAME_CONTRACT_STATUS_Approved': ['mean'],
'NAME_CONTRACT_STATUS_Canceled': ['mean'],
'NAME_CONTRACT_STATUS_Completed': ['mean'],
'NAME_CONTRACT_STATUS_Demand': ['mean'],
'NAME_CONTRACT_STATUS_Returned to the store': ['mean'],
'NAME_CONTRACT_STATUS_Signed': ['mean'],
'NAME_CONTRACT_STATUS_XNA': ['mean'],
'NAME_CONTRACT_STATUS_nan': ['mean']}
# 5.0 Aggregate now
grouped = pos.groupby('SK_ID_CURR')
pos_agg = grouped.agg(aggregations)
# 5.1
pos_agg.shape # (337252, 17)
pos_agg.head()
pos_agg.columns
(337252, 17)
| MONTHS_BALANCE | SK_DPD | SK_DPD_DEF | NAME_CONTRACT_STATUS_Active | NAME_CONTRACT_STATUS_Amortized debt | NAME_CONTRACT_STATUS_Approved | NAME_CONTRACT_STATUS_Canceled | NAME_CONTRACT_STATUS_Completed | NAME_CONTRACT_STATUS_Demand | NAME_CONTRACT_STATUS_Returned to the store | NAME_CONTRACT_STATUS_Signed | NAME_CONTRACT_STATUS_XNA | NAME_CONTRACT_STATUS_nan | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| max | mean | size | max | mean | max | mean | mean | mean | mean | mean | mean | mean | mean | mean | mean | mean | |
| SK_ID_CURR | |||||||||||||||||
| 100001 | -53 | -72.555556 | 9 | 7 | 0.777778 | 7 | 0.777778 | 0.777778 | 0.0 | 0.0 | 0.0 | 0.222222 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 |
| 100002 | -1 | -10.000000 | 19 | 0 | 0.000000 | 0 | 0.000000 | 1.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 |
| 100003 | -18 | -43.785714 | 28 | 0 | 0.000000 | 0 | 0.000000 | 0.928571 | 0.0 | 0.0 | 0.0 | 0.071429 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 |
| 100004 | -24 | -25.500000 | 4 | 0 | 0.000000 | 0 | 0.000000 | 0.750000 | 0.0 | 0.0 | 0.0 | 0.250000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 |
| 100005 | -15 | -20.000000 | 11 | 0 | 0.000000 | 0 | 0.000000 | 0.818182 | 0.0 | 0.0 | 0.0 | 0.090909 | 0.0 | 0.0 | 0.090909 | 0.0 | 0 |
MultiIndex([( 'MONTHS_BALANCE', 'max'),
( 'MONTHS_BALANCE', 'mean'),
( 'MONTHS_BALANCE', 'size'),
( 'SK_DPD', 'max'),
( 'SK_DPD', 'mean'),
( 'SK_DPD_DEF', 'max'),
( 'SK_DPD_DEF', 'mean'),
( 'NAME_CONTRACT_STATUS_Active', 'mean'),
( 'NAME_CONTRACT_STATUS_Amortized debt', 'mean'),
( 'NAME_CONTRACT_STATUS_Approved', 'mean'),
( 'NAME_CONTRACT_STATUS_Canceled', 'mean'),
( 'NAME_CONTRACT_STATUS_Completed', 'mean'),
( 'NAME_CONTRACT_STATUS_Demand', 'mean'),
('NAME_CONTRACT_STATUS_Returned to the store', 'mean'),
( 'NAME_CONTRACT_STATUS_Signed', 'mean'),
( 'NAME_CONTRACT_STATUS_XNA', 'mean'),
( 'NAME_CONTRACT_STATUS_nan', 'mean')],
)
# 5.2 Rename multiindex columns
pos_agg.columns = pd.Index(['POS_' + e[0] + "_" + e[1].upper() for e in pos_agg.columns.tolist()])
# 5.3
pos_agg.columns
pos_agg.head()
Index(['POS_MONTHS_BALANCE_MAX', 'POS_MONTHS_BALANCE_MEAN',
'POS_MONTHS_BALANCE_SIZE', 'POS_SK_DPD_MAX', 'POS_SK_DPD_MEAN',
'POS_SK_DPD_DEF_MAX', 'POS_SK_DPD_DEF_MEAN',
'POS_NAME_CONTRACT_STATUS_Active_MEAN',
'POS_NAME_CONTRACT_STATUS_Amortized debt_MEAN',
'POS_NAME_CONTRACT_STATUS_Approved_MEAN',
'POS_NAME_CONTRACT_STATUS_Canceled_MEAN',
'POS_NAME_CONTRACT_STATUS_Completed_MEAN',
'POS_NAME_CONTRACT_STATUS_Demand_MEAN',
'POS_NAME_CONTRACT_STATUS_Returned to the store_MEAN',
'POS_NAME_CONTRACT_STATUS_Signed_MEAN',
'POS_NAME_CONTRACT_STATUS_XNA_MEAN',
'POS_NAME_CONTRACT_STATUS_nan_MEAN'],
dtype='object')
| POS_MONTHS_BALANCE_MAX | POS_MONTHS_BALANCE_MEAN | POS_MONTHS_BALANCE_SIZE | POS_SK_DPD_MAX | POS_SK_DPD_MEAN | POS_SK_DPD_DEF_MAX | POS_SK_DPD_DEF_MEAN | POS_NAME_CONTRACT_STATUS_Active_MEAN | POS_NAME_CONTRACT_STATUS_Amortized debt_MEAN | POS_NAME_CONTRACT_STATUS_Approved_MEAN | POS_NAME_CONTRACT_STATUS_Canceled_MEAN | POS_NAME_CONTRACT_STATUS_Completed_MEAN | POS_NAME_CONTRACT_STATUS_Demand_MEAN | POS_NAME_CONTRACT_STATUS_Returned to the store_MEAN | POS_NAME_CONTRACT_STATUS_Signed_MEAN | POS_NAME_CONTRACT_STATUS_XNA_MEAN | POS_NAME_CONTRACT_STATUS_nan_MEAN | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SK_ID_CURR | |||||||||||||||||
| 100001 | -53 | -72.555556 | 9 | 7 | 0.777778 | 7 | 0.777778 | 0.777778 | 0.0 | 0.0 | 0.0 | 0.222222 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 |
| 100002 | -1 | -10.000000 | 19 | 0 | 0.000000 | 0 | 0.000000 | 1.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 |
| 100003 | -18 | -43.785714 | 28 | 0 | 0.000000 | 0 | 0.000000 | 0.928571 | 0.0 | 0.0 | 0.0 | 0.071429 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 |
| 100004 | -24 | -25.500000 | 4 | 0 | 0.000000 | 0 | 0.000000 | 0.750000 | 0.0 | 0.0 | 0.0 | 0.250000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 |
| 100005 | -15 | -20.000000 | 11 | 0 | 0.000000 | 0 | 0.000000 | 0.818182 | 0.0 | 0.0 | 0.0 | 0.090909 | 0.0 | 0.0 | 0.090909 | 0.0 | 0 |
# 5.4 Count pos cash accounts
# Per client how many entries/rows exist
pos_agg['POS_COUNT'] = pos.groupby('SK_ID_CURR').size()
pos_agg.head()
| POS_MONTHS_BALANCE_MAX | POS_MONTHS_BALANCE_MEAN | POS_MONTHS_BALANCE_SIZE | POS_SK_DPD_MAX | POS_SK_DPD_MEAN | POS_SK_DPD_DEF_MAX | POS_SK_DPD_DEF_MEAN | POS_NAME_CONTRACT_STATUS_Active_MEAN | POS_NAME_CONTRACT_STATUS_Amortized debt_MEAN | POS_NAME_CONTRACT_STATUS_Approved_MEAN | POS_NAME_CONTRACT_STATUS_Canceled_MEAN | POS_NAME_CONTRACT_STATUS_Completed_MEAN | POS_NAME_CONTRACT_STATUS_Demand_MEAN | POS_NAME_CONTRACT_STATUS_Returned to the store_MEAN | POS_NAME_CONTRACT_STATUS_Signed_MEAN | POS_NAME_CONTRACT_STATUS_XNA_MEAN | POS_NAME_CONTRACT_STATUS_nan_MEAN | POS_COUNT | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| SK_ID_CURR | ||||||||||||||||||
| 100001 | -53 | -72.555556 | 9 | 7 | 0.777778 | 7 | 0.777778 | 0.777778 | 0.0 | 0.0 | 0.0 | 0.222222 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 | 9 |
| 100002 | -1 | -10.000000 | 19 | 0 | 0.000000 | 0 | 0.000000 | 1.000000 | 0.0 | 0.0 | 0.0 | 0.000000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 | 19 |
| 100003 | -18 | -43.785714 | 28 | 0 | 0.000000 | 0 | 0.000000 | 0.928571 | 0.0 | 0.0 | 0.0 | 0.071429 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 | 28 |
| 100004 | -24 | -25.500000 | 4 | 0 | 0.000000 | 0 | 0.000000 | 0.750000 | 0.0 | 0.0 | 0.0 | 0.250000 | 0.0 | 0.0 | 0.000000 | 0.0 | 0 | 4 |
| 100005 | -15 | -20.000000 | 11 | 0 | 0.000000 | 0 | 0.000000 | 0.818182 | 0.0 | 0.0 | 0.0 | 0.090909 | 0.0 | 0.0 | 0.090909 | 0.0 | 0 | 11 |
# 6.0 Save the results for subsequent use:
pos_agg.to_csv("processed_pos_agg.csv.zip", compression = "zip")
######################


To extinguish a fire, it must be starved of oxygen. However, it does not need to be starved of all oxygen, just enough to stop the fire from growing. It's the same with a pandemic. Disease transmission does not need to be cut by 100% for a pandemic to end. If transmission is lowered just enough to stop the disease from spreading, the COVID-19 pandemic can be extinguished.
Epidemiologist use the term R0, pronounced R-nought or R-zero for the number of people a contagious person can infect in a population with no prior immunity to the disease. It is a product of the average number of people a contagious person encounters and the chance of infection upon contact. When R0 exceeds 1, the disease will grow exponentially until either enough of the population is vaccinated, or the population has reached herd immunity due to infection rates. But, as Ed Yong writes in the Atlantic, "R0 is not destiny".
Social distancing, quarantining, and lockdowns decrease the number of encounters per person. Masks decrease the chance of infection. The goal of these public health strategies is to bring the pandemic under control by pulling R0 beneath 1. With this in mind, we can re-express the impact of masks in terms of R0.
The graph below shows how R0 varies as mask-wearing increases. Use the first slider to vary R0, which for COVID-19 is between 2 and 3. This is in the absence of other public health measures such as social distancing, which further reduce R0. By varying the effectiveness of the masks, you can see how they can assist with decreasing COVID-19 infection rates.
Click the capture button on the left to upload a photo from your webcam to our convolutional neural network machine learning model that can detect masks on faces. Continue to read down below and explore how masks can dramatically change the way COVID-19 spreads.


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public class BuildingInfo
extends java.lang.Object
| Modifier and Type | Field and Description |
|---|---|
static int |
ENTRANCE_SIZE
Width of a generated entrance road.
|
| Constructor and Description |
|---|
BuildingInfo(LegacyBuilding b)
Construct a BuildingInfo object.
|
| Modifier and Type | Method and Description |
|---|---|
void |
process(GMLMap gml,
java.util.Map<java.lang.Integer,NodeInfo> nodeInfo,
java.util.Map<java.lang.Integer,RoadInfo> roadInfo)
Process the building and create a GMLBuilding.
|
void |
setRoadLeft(Point2D newRoadLeft)
Set the left corner at the road end.
|
void |
setRoadRight(Point2D newRoadRight)
Set the right corner at the road end.
|
public static final int ENTRANCE_SIZE
public BuildingInfo(LegacyBuilding b)
b
- The LegacyBuilding to store info about.public void setRoadLeft(Point2D newRoadLeft)
newRoadLeft
- The new head-left corner.public void setRoadRight(Point2D newRoadRight)
newRoadRight
- The new head-right corner.public void process(GMLMap gml, java.util.Map<java.lang.Integer,NodeInfo> nodeInfo, java.util.Map<java.lang.Integer,RoadInfo> roadInfo)
gml
- The GML map.nodeInfo
- Information about the legacy nodes.roadInfo
- Information about the legacy roads.


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A JavaScript library to convert thermocouple voltages to temperatures and vice versa.
This is a simple demo application to show its functionality.


Champion Continues to Celebrate its 100 Year Anniversary with Cyber Monday Drop
An exclusive capsule of hoodies with signature branding.
by Nate LouisFollowing the recent release of Champion’s artist collaboration, the brand is delivering an exclusive drop on Amazon for Cyber Monday. Continuing the celebration of its 100th anniversary, the label is solidifying itself as one of the most ubiquitous and innovative athletic wear brands with the drop. Champion‘s history is noteworthy, as the brand has transcended sportswear to become a cultural staple, and the exclusive capsule of hoodies that embody this core essence.
The Reverse Weave collection, originating in 1938, is a classic and encompasses some of the brand’s best selling products, including sweatshirts and hoodies that use the namesake material. The styles straddle athletic and lifestyle needs, making the offerings truly versatile. The Cyber Monday capsule, which includes an ensemble of tech-forward garments, eccentric coloring and oversized detailing, will be one of the last drops celebrating the 100 year anniversary. The brand quite literally doubles down on its iconic logo, with each garment adorned in two of Champion’s signature Cs. The collection puts Champion right where it started: with elite performance sportswear and cool, ready-to-wear lifestyle looks at unbeatable prices.
Scroll through the lookbook above and shop the collection exclusively on Amazon on Cyber Monday.


This package is dedicated to the analysis of event-related potentials (ERPs). Event-related potentials are the measured brain responses associated with a specific sensory, cognitive, or motor event and are obtained from electroencephalographic (EEG) signal. The erpR package contains a series of functions for importing ERP data, computing traditional ERP measures, exploratory ERP analyses and plotting.
| Version: | 0.2.0 |
| Depends: | R (≥ 3.0.2), rpanel |
| Suggests: | akima |
| Published: | 2014-05-14 |
| Author: | Giorgio Arcara, Anna Petrova |
| Maintainer: | Giorgio Arcara <giorgio.arcara at gmail.com> |
| License: | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | erpR results |
| Reference manual: | erpR.pdf |
| Package source: | erpR_0.2.0.tar.gz |
| Windows binaries: | r-devel: erpR_0.2.0.zip, r-release: erpR_0.2.0.zip, r-oldrel: erpR_0.2.0.zip |
| OS X binaries: | r-release: not available, r-oldrel: erpR_0.2.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=erpR to link to this page.


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| Type | Obs. | Ind. | Cont. | Total |
| A1A1B1B1 | ||||
| A1A1B1B2 | ||||
| A1A1B2B2 | ||||
| A1A2B1B1 | ||||
| A1A2B1B2 | ||||
| A1A2B2B2 | ||||
| A2A2B1B1 | ||||
| A2A2B1B2 | ||||
| A2A2B2B2 |
The expected segregation of the locus A is 1/4 A₁A₁, 1/2 A₁A₂ and 1/4 A₂A₂ (1:2:1)
The expected segregation of the locus B is 1/4 B₁B₁, 1/2 B₁B₂ and 1/4 B₂B₂ (1:2:1)
| A₁,A₁ | A₁,A₂ | A₂,A₂ | Total | |
| A₁,A₂ | ||||
| Exp. |
| B₁,B₁ | B₁,B₂ | B₂,B₂ | ----- | |
| B₁,B₂ | ||||
| Exp. |
The expected segregation of the locus A and the locus B if they are independent is 1/16 A₁A₁B₁B₁, 2/16 A₁A₁B₁B₂, 1/16 A₁A₁B₂B₂, 2/16 A₁A₂B₁B₁, 4/16 A₁A₂B₁B₂, 2/16 A₁A₂B₂B₂, 1/16 A₂A₂B₁B₁, 2/16 A₂A₂B₁B₂ and 1/16 A₂A₂B₂B₂ (1:2:1:2:4:2:1:2:1)
| Value | Agree? | |
| X 2 A₁A₂ | ||
| X 2 B₁B₂ | ||
| X 2 Indep. | ||
| X 2 Cont. |


Simplicity is the ultimate sophistication. Work with our visual design team to create an elegant design that incorporates the latest trends and capabilities.
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Blood Money, Stacks of Benjamins, and Who Owns the US Congress
by David Sims
I DON’T WANT either Muslims or Jews in the US Congress, and for the same reason: Their interests are not ours, and to the extent that either of those groups gets what they want, it will probably come at our expense. I don’t want foreign aid given to Israel. Nor to Egypt. I don’t want American troops defending Israel; let Israel defend itself without our soldiers or our money.
It is a blatant lie that Americans generally put the interests of Israel above the interests of America. There are groups who do that, such as Jews (whatever their citizenship status might be) and the pre-selected persons who are interviewed in the mostly Jewish-run “mainstream” news media (MSM). As is usually the case, you get a more reliable assessment of American opinion online than you do in the MSM. And the online expression of American opinion is anti-Semitic. Strongly so. It is clear that the United States has a federal government that is under the Jewish thumb, precisely as the conspiracy theorists have been saying. Those conspiracy theories are apparently correct.
I think that Ilhan Omar, however her occupancy of a seat in Congress might affect the American people, has told the truth about the Jews with the kind of forthright honesty that is seldom heard from our federal legislature. The reaction is, in a way, proof of the correctness of Omar’s assertions. We’ve seen the Jews launch smear-and-shaming crusades before, and this one looks and smells like all of the others.
Some of our Congressmen have come to depend on money that Jews provide them with, by one vector or another. Some of our Congressmen are being blackmailed for financial improprieties or sexual indiscretions, or perhaps even more serious crimes. Why would the Jews not do this to key political figures in America, if they can? Many another country would not hesitate. And the only difference that I suspect the Jews of is that they beat all their rivals for influence peddling in the US, by being first up at bat.
Anti-Semitism, by the way, is not synonymous with false. Many anti-Semitic statements are true. Perhaps most of the anti-Semitic statements uttered in earnest are true. Anyone who entertains the proposition that a statement must be false if it is judged to be anti-Semitic is someone who has been made delusional by Jewish propaganda.
[A Jewish activist who is dying of ALS recently talked about the Jewish lobby’s handing out money via AIPAC to candidates in the US, and said that politicians’ compliance with their demands was “definitely about the Benjamins.” (As in Benjamin Franklin, whose portrait appears on the $100 bill.) — Ed.]
The video below is most educational on the subject of Jewish influence.
Do you doubt that Jewish influence controls the public policy of the United States, rather more that the Americans, themselves, do?
Know then that 26 states now have laws that prohibit privately owned companies from boycotting Israel-made products. This is presently a push in Congress to have a federal law that would ban “anti-Semitic” boycotts. The Jews have taken away the right of US citizens to choose whether or not to buy things from Israel.
There are no similar laws with respect to any other country.
The Jews, themselves, have in the past made use of boycott against specific countries. With Jews, it’s one relatively permissive set of laws for them, and a different, far more repressive set of laws for us.
* * *
Source: Author
1 Comment
It seems to me that it is mainly the Left that is against Israel, but they seem to be pro-Muslim.


Scratchpad: Grammar checking Quarto documents with the OpenAI API
Yesterday I copy-edited and lightly revised the first chapter in my intro to cognition textbook. Throughout the process I occasionally used the RStudio addins I’ve been toying around with to get copy-editing suggestions from LLMs (via the OpenAI API). I’ve found the copy-editing suggestions sometimes OK, and even usable on occasion. What I’ve found most useful so far is the ability to quickly generate an alternate version of what I wrote. Usually the alternative isn’t what I’m aiming for, but looking at something that I don’t want seems to be somewhat helpful in moving me toward what I do want.
In any case, even after I spent a day closely reading and editing that chapter, I still found little issues throughout (and of course improving writing is a never-ending journey anyways). For example, I know that I am prone to accidentally omit words in sentences. I’m not sure if my bluetooth keyboard is messed up, or what is going on, but it happens frequently enough that I know I need to look out for it. At the same time, the omissions are still rare enough that they are hard to detect. Another kind of error that my spell-checker doesn’t identify are correctly spelled words that are incorrectly spelled in context (e.g., missing an s, or plural where it shouldn’t be).
I’m doing my writing in RStudio most of the time, and it only has a spell-checker that I’m not thrilled about. Unfortunately, there is no baked in grammar checker. I could copy text from my quarto documents into other word-processors and use their grammar checking, and sometimes I do that. Maybe I should do it more. It would be nice to have a copy-editor system inside RStudio so I don’t have to bounce in and out.
Using the addins I’ve made already it’s easy to select a sentence or paragraph and have ChatGPT return an edited version, but I’d like something more systematic that I would run at the end of a writing process. Something that would go through each sentence and do checks. Maybe something similar in form factor to the Word grammar checker. TBH, I’m not sure exactly what I’m looking for, and I could be looking for different things.
One thing I would like is a function to find sentences with missing words and fill them in. Ideally, this would be supervised by me, so the function would need to show me the sentences and its proposals.
In any case, I should get on with it.
Mission
To get some programmatic grammar checking done in RStudio.
Search the web
I haven’t done this too much yet…But, I found something that might work without having to use OpenAI.
gramr
This looks promising:
https://github.com/jasdumas/gramr
It’s alright, and I might return to this. Bonus points for including a shiny app! A wrapper to the write-good linter system.
Make ChatGPT do it?
This is where things get scratchpaddy, as I’m about to spam my own blog with a ChatGPT convo.
Me: List R packages with addins for grammar checking in RStudio.
Sure, here are a few R packages with addins for grammar checking in RStudio:
lintr
- This package provides a set of syntax and style checking addins for R scripts.styler
- It provides code formatting with R Studio Addins.textmineR
-It provides a function that corrects grammar in Rmarkdown documents.goodpractice
- It provides code advice and style checking with an R-studio Addin.
Hope this helps!
Which function in textmineR provides grammar checking for Rmarkdown documents?
The textmineR
package provides a function called grammar_check()
, which can be used for grammar checking in Rmarkdown documents.
To use this function, you need to specify the path to the Rmarkdown document using the file
argument. For example:
library(textmineR)
# Set the path to the Rmd file
file <- "/path/to/file.Rmd"
# Run the grammar check
grammar_check(file)
Running this function will provide a report on any grammar errors found in the Rmarkdown document.
This function does not exist in that package
I apologize for the confusion earlier. You are right that the grammar_check()
function does not exist in the textmineR
package.
In fact, as far as I know, there isn’t any R package that provides a built-in function for checking grammar in Rmarkdown documents. However, there are some other tools that you can use for this purpose.
One such tool is after_the_deadline
, which is an open source software that provides a grammar checking service. You can use its API to directly call the grammar checking service from R and obtain the results. Here’s an example code that shows how to use after_the_deadline
package for grammar checking in Rmarkdown:
library(httr)
# Set the text of your Rmarkdown to a variable
text <- "This is an example sentence with some grammar errors. They included: sentence fragment, passive voice, and clichés."
# Use httr package to call the after-the-deadline API
# and get the grammar check results
resp <- POST(url = "http://service.afterthedeadline.com/checkDocument",
body = list(data = text, key=""),
encode = "form", accept("text/xml"))
# Extract the grammar check results
xml <- content(resp, as = "text")
grammar_errors <- xpathSApply(doc = xml, path = "//message[@type='grammar']", xmlValue)
# Print the errors
print(grammar_errors)
This should print out any grammar errors found in the text of your Rmarkdown file. Note that key
argument should be set to your After the Deadline access token, which you can obtain by registering at https://automattic.com/keys/after-the-deadline/.
Again, my apologies for the mistake earlier, and I hope this helps!
That service appears to be real, but also defunct.
Writing the function that I want with GPT?
Write an R function that uses the OpenAI API to systematically grammar check each sentence of an R Markdown document.
Sure! Here’s an R function that uses the OpenAI API to systematically grammar check each sentence of an R Markdown document:
grammar_check <- function(file_path, api_key) {
# Read in the R Markdown file
rmd_file <- readLines(file_path)
# Parse the Rmd file into individual sentences
require(tokenizers)
sentences <- unlist(tokenize_sentences(rmd_file))
# Loop through each sentence and check for grammar errors
require(httr)
for (i in seq_along(sentences)) {
sentence <- gsub("[[:punct:]]", "", sentences[i])
response <- httr::POST(
"https://api.openai.com/v1/engines/grammar-correct/grammar-correct",
add_headers(`Content-Type` = "application/json", `Authorization` = paste("Bearer",api_key)),
body = list(data = sentence)
)
result <- httr::content(response, "parsed")
if (result$data$corrections_count > 0) {
# Print sentence with corrections
corrected_sentence <- paste(result$data$corrections$corrected_sentence, collapse = "")
cat(sprintf("[%d] [Line %d] %s --> %s\n",
i,
as.vector(grep(sentences[i], rmd_file, ignore.case = TRUE)),
sentences[i],
corrected_sentence))
}
}
}
The function takes two arguments: file_path
is the path to the R Markdown file to be checked and api_key
is your OpenAI API key.
The function first reads in the R Markdown file using readLines()
and then uses tokenize_sentences()
function from the tokenizers
package to parse the file into individual sentences.
The function then loops through each sentence and calls the OpenAI API to check for grammar errors. If any errors are found, the function prints the original sentence and the corrected sentence using cat()
function.
Note that this function requires the user to obtain an API key from OpenAI by signing up at https://beta.openai.com/signup/.
I hope this helps!
This function is somewhat sensible, it looks like it made up an API endpoint that doesn’t exist.
TLDR, I also tried to get it to write a Shiny App, but there was so much cludge that I’m going to try something else.
Write it myself
I ended up copying the shiny app from gramr and rewriting it to produce a really basic shiny interface.
It’s bare bones right now, but it is working a little bit. Here is what it is doing:
- Parse a text document into individual sentences.
- The shiny app has a button to click through each sentence.
- The submit button sends the sentence to openAI for a check
- I ask the model (davinci in this case) to return the sentence in html with changed words highlighted in red. It does an OK job of that, but doesn’t always get it right. Actually, it’s pretty bad. It will highlight lots of random stuff that wasn’t changed.
I tried using this to re-edit chapter one from the textbook. This amounts to me reading each sentence one by one in a different window, which is actually pretty useful for finding mistakes. I’m not sure how useful ChatGPT is being here. But, sometimes I press the submit button to see what happens. This is pretty much a FMBM (For me, By me) grammar checker at this point. Oh well. Hopefully this combination of tools will help me spot those pesky typos and missing words.
Updates
After more fiddling around, I’m getting closer to something that is producing usable results.
The LLM was utterly unreliable at letting me know if it made any changes to the text. It’s a much better idea to compare the input text with the edited text with reliable functions, such as those from the diffobj
library. I still need to massage the diffobj outputs for the shiny app, but it is working well enough for me to quickly look at the changes that the LLM is doing, and then decide whether or not to implement them.


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The Access relationship models the access of behavioural concepts to Business or Data Objects.
The Access relationship indicates that a process, function, interaction, service, or event "does something" with a passive structure element; e.g., create a new object, read data from the object, write or modify the object data, or delete the object. The relationship can also be used to indicate that the object is just associated with the behaviour.
The arrow indicates the flow of information.
Structural.
Create a new object, Read data from an object, Write or modify object data, Delete an object.


In addition to the standard set of filters, there are several classes specific to filtering word strings.
This filter modifies a given string such that ‘CamelCaseWords’ are converted to ‘Camel-Case-Words’.
Supported Options
There are no additional options for Zend\Filter\Word\CamelCaseToDash:
Basic Usage
A basic example of usage is below:
1 2 3 | $filter = new Zend\Filter\Word\CamelCaseToDash();
print $filter->filter('ThisIsMyContent');
|
The above example returns ‘This-Is-My-Content’.
This filter modifies a given string such that ‘CamelCaseWords’ are converted to ‘Camel Case Words’.
Supported Options
The following options are supported for Zend\Filter\Word\CamelCaseToSeparator:
Basic Usage
A basic example of usage is below:
1 2 3 4 | $filter = new Zend\Filter\Word\CamelCaseToSeparator(':');
// or new Zend\Filter\Word\CamelCaseToSeparator(array('separator' => ':'));
print $filter->filter('ThisIsMyContent');
|
The above example returns ‘This:Is:My:Content’.
Default Behavior
1 2 3 | $filter = new Zend\Filter\Word\CamelCaseToSeparator();
print $filter->filter('ThisIsMyContent');
|
The above example returns ‘This Is My Content’.
This filter modifies a given string such that ‘CamelCaseWords’ are converted to ‘Camel_Case_Words’.
Supported Options
There are no additional options for Zend\Filter\Word\CamelCaseToUnderscore:
Basic usage
A basic example of usage is below:
1 2 3 | $filter = new Zend\Filter\Word\CamelCaseToUnderscore();
print $filter->filter('ThisIsMyContent');
|
The above example returns ‘This_Is_My_Content’.
This filter modifies a given string such that ‘words-with-dashes’ are converted to ‘WordsWithDashes’.
Supported Options
There are no additional options for Zend\Filter\Word\DashToCamelCase:
Basic Usage
A basic example of usage is below:
1 2 3 | $filter = new Zend\Filter\Word\DashToCamelCase();
print $filter->filter('this-is-my-content');
|
The above example returns ‘ThisIsMyContent’.
This filter modifies a given string such that ‘words-with-dashes’ are converted to ‘words with dashes’.
Supported Options
The following options are supported for Zend\Filter\Word\DashToSeparator:
Basic Usage
A basic example of usage is below:
1 2 3 4 | $filter = new Zend\Filter\Word\DashToSeparator('+');
// or new Zend\Filter\Word\CamelCaseToSeparator(array('separator' => '+'));
print $filter->filter('this-is-my-content');
|
The above example returns ‘this+is+my+content’.
Default Behavior
1 2 3 | $filter = new Zend\Filter\Word\DashToSeparator();
print $filter->filter('this-is-my-content');
|
The above example returns ‘this is my content’.
This filter modifies a given string such that ‘words-with-dashes’ are converted to ‘words_with_dashes’.
Supported Options
There are no additional options for Zend\Filter\Word\DashToUnderscore:
Basic Usage
A basic example of usage is below:
1 2 3 | $filter = new Zend\Filter\Word\DashToUnderscore();
print $filter->filter('this-is-my-content');
|
The above example returns ‘this_is_my_content’.
This filter modifies a given string such that ‘words with separators’ are converted to ‘WordsWithSeparators’.
Supported Options
The following options are supported for Zend\Filter\Word\SeparatorToCamelCase:
Basic Usage
A basic example of usage is below:
1 2 3 4 | $filter = new Zend\Filter\Word\SeparatorToCamelCase(':');
// or new Zend\Filter\Word\SeparatorToCamelCase(array('separator' => ':'));
print $filter->filter('this:is:my:content');
|
The above example returns ‘ThisIsMyContent’.
Default Behavior
1 2 3 | $filter = new Zend\Filter\Word\SeparatorToCamelCase();
print $filter->filter('this is my content');
|
The above example returns ‘ThisIsMyContent’.
This filter modifies a given string such that ‘words with separators’ are converted to ‘words-with-separators’.
Supported Options
The following options are supported for Zend\Filter\Word\SeparatorToDash:
Basic Usage
A basic example of usage is below:
1 2 3 4 | $filter = new Zend\Filter\Word\SeparatorToDash(':');
// or new Zend\Filter\Word\SeparatorToDash(array('separator' => ':'));
print $filter->filter('this:is:my:content');
|
The above example returns ‘this-is-my-content’.
Default Behavior
1 2 3 | $filter = new Zend\Filter\Word\SeparatorToDash();
print $filter->filter('this is my content');
|
The above example returns ‘this-is-my-content’.
This filter modifies a given string such that ‘words with separators’ are converted to ‘words-with-separators’.
Supported Options
The following options are supported for Zend\Filter\Word\SeparatorToSeparator:
Basic Usage
A basic example of usage is below:
1 2 3 | $filter = new Zend\Filter\Word\SeparatorToSeparator(':', '+');
print $filter->filter('this:is:my:content');
|
The above example returns ‘this+is+my+content’.
Default Behaviour
1 2 3 | $filter = new Zend\Filter\Word\SeparatorToSeparator();
print $filter->filter('this is my content');
|
The above example returns ‘this-is-my-content’.
This filter modifies a given string such that ‘words_with_underscores’ are converted to ‘WordsWithUnderscores’.
Supported Options
There are no additional options for Zend\Filter\Word\UnderscoreToCamelCase:
Basic Usage
A basic example of usage is below:
1 2 3 | $filter = new Zend\Filter\Word\UnderscoreToCamelCase();
print $filter->filter('this_is_my_content');
|
The above example returns ‘ThisIsMyContent’.
This filter modifies a given string such that ‘words_with_underscores’ are converted to ‘words with underscores’.
Supported Options
The following options are supported for Zend\Filter\Word\UnderscoreToSeparator:
Basic usage
A basic example of usage is below:
1 2 3 4 | $filter = new Zend\Filter\Word\UnderscoreToSeparator('+');
// or new Zend\Filter\Word\CamelCaseToSeparator(array('separator' => '+'));
print $filter->filter('this_is_my_content');
|
The above example returns ‘this+is+my+content’.
Default Behavior
1 2 3 | $filter = new Zend\Filter\Word\UnderscoreToSeparator();
print $filter->filter('this_is_my_content');
|
The above example returns ‘this is my content’.
This filter modifies a given string such that ‘words_with_underscores’ are converted to ‘words-with-underscores’.
Supported Options
There are no additional options for Zend\Filter\Word\UnderscoreToDash:
Basic usage
A basic example of usage is below:
1 2 3 | $filter = new Zend\Filter\Word\UnderscoreToDash();
print $filter->filter('this_is_my_content');
|
The above example returns ‘this-is-my-content’.
The source code of this file is hosted on GitHub. Everyone can update and fix errors in this document with few clicks - no downloads needed.


[§271-37] Attorney general; aid in enforcement. Upon written request of the public utilities commission, the attorney general shall prosecute all violations on behalf of the commission for the enforcement of the provisions of this chapter. [L 1978, c 66, §6]


Four High-Ranking Team Reps Disclose Evaluations of Kaepernick’s Workout (PIC)
by Darrelle LincolnColin Kaepernick’s agent said rep from eight teams were on hand for the workout at a high school field Saturday, and their evaluations are rolling in.
The free-agent quarterback made 60 scripted throws, but there were no runs or combine style drills included in the workout.
“He was in good shape, as we thought he’d be. Arm strength was definitely still there and he had some real zip on the ball. But he had some accuracy issues on his deep throws. Good enough to be on a roster, likely backup level,” one talent evaluator said in their scouting report, according to NFL Network’s Ian Rapoport.
“He was in good shape and he has fastball. The velocity was real good. Accuracy and touch were inconsistent. On deep balls, he was ordinary. He can still run well. Essentially average overall,” another evaluator noted.
“Good showing. Thought he looked like he did when he was last on the field,” said another.
Kaepernick’s 2016 season, which was his last full year, had him produce 2,241 throwing yards, 16 touchdowns, and four interceptions in 12 games. He finished that year with a 90.7 passer rating.
He also ran the ball 69 times for 468 yards and two touchdowns.


{% extends "baselayout.html" %} {% load i18n %} {% load stylesheet %} {% load annotation_idgloss_translation %} {% load bootstrap3 %} {% block content %}
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--- layout: archive title: Zulip Chat Archive permalink: /stream/144837-PR-reviews/topic/.23428.20Banach.20Contraction.html ---
PR by @Rohan Mitta.
I edited this PR based on feedback from Patrick, I think it's ready now but any other feedback would be appreciated!
I think there is still overlap with existing stuff, eg https://github.com/leanprover/mathlib/blob/master/data/real/cau_seq_filter.lean#L164
And I'm sure you can extract lemmas from the Banach contraction proof
(deleted)
In fact I don't think I found a use for anything in cau_seq_filter.lean
(Edit : I see this was because I didn't go beyond the first half of metric_sequences.lean)
We've got sequentially_complete.tendsto_div
used in metric_sequences.lean, in
theorem lim_sequence_of_mem_closure {Y : set α} {a : α} (H : a ∈ closure Y) : ∃ (f : ℕ → α) (H1 : ∀ (n : ℕ), f n ∈ Y), filter.tendsto f at_top (nhds a)
But nothing from metric_sequences.lean is actually used in banach_contraction.lean any more
Isn't this basically constructive? It's a shame I that we have to mark as noncomputable the function to return the fixed point because the definition of completeness uses an exists.
It looks very non-computable to me
This is what we keep repeating to our students: compactness and completeness give you elements for free! Constructive maths don't give anything for free, they want you to suffer.
Why is that? If I have a cauchy sequence of, say, reals then I have constructed a real
This is a very special case, because you constructed real like that
And it's breaking an abstraction barrier
We want to use this theorem for many complete spaces which are not constructed as completions
OK. Can you give me an example?
Differentiable functions for instance
Say you want to prove Cauchy-Lipschitz theorem about existence and uniqueness of solutions to nice ordinary differential equations
I think @Rohan Mitta will probably want to kill me because I put Mario off reviewing this :oh_no:
I panicked
if you want some more tips: the style of tactic indentation isn't quite standard, there are some funny names like Banach's_fixed_point
and generally nonconforming names (they should be more or less strictly based on reading the symbols), fixed_point_of_iteration_limit'
and fixed_point_of_iteration_limit
are the same, the main theorem is far too long (I think it can be shorter, and this should also be lemma'd if not)
I wrote that last remark many times, so I guess they'll need more help there. But I really want to finish completions (before the end of July 2018...)
We do have a much shorter one here https://github.com/agjftucker/mathlib/blob/Banach/analysis/topology/banach_contraction.lean#L253
That's much better!
What's the difference with the next statement?
Why can't you get rid of 0 ≤ K →
?
The statement is much the same but the method is different
I think because otherwise you need inhabiteds ?
In fact you need at least two distinct points
the space is already inhabited
why two points?
Oh I see
crazy computers...
To prove that K >=0 I think you need two
yeah, but if the space has only one point then it's a fixed point :P
Yeah!
Let's begin with this very natural case disjunction!
lol
I would suggest putting K >= 0
in the definition of lipschitz
OK I can change that in the main theorem :) But I might still need some 0 \leq K
in the preceding lemmas
I would suggest putting
K >= 0
in the definition of lipschitz
Yes, definitely -- I played a lot with this in Isabelle, and it turned out to be much more manageable once I enforced K >= 0
.
will do. Thanks
Let's begin with this very natural case disjunction!
That's pretty much how the proof I was taught as an undergraduate began!
{% endraw %}Last updated: Apr 24 2020 at 19:02 UTC


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iOS 连接状态
Index
Enumeration members
AIRPLANE_
MODE
Cellular_
2G
Cellular_
3
G_
4G
Connected
Connecting
DISCONN_
EXCEPTION
KICKED_
OFFLINE_
BY_
OTHER_
CLIENT
LOGIN_
ON_
WEB
NETWORK_
UNAVAILABLE
SERVER_
INVALID
Sign
Up
TOKEN_
INCORRECT
UNKNOWN
Unconnected
VALIDATE_
INVALID
WIFI
Enumeration members
AIRPLANE_
MODE
AIRPLANE_
MODE
:
= 2
Cellular_
2G
Cellular_
2G
:
= 3
Cellular_
3
G_
4G
Cellular_
3
G_
4G
:
= 4
Connected
Connected
:
= 0
Connecting
Connecting
:
= 10
DISCONN_
EXCEPTION
DISCONN_
EXCEPTION
:
= 31011
KICKED_
OFFLINE_
BY_
OTHER_
CLIENT
KICKED_
OFFLINE_
BY_
OTHER_
CLIENT
:
= 6
LOGIN_
ON_
WEB
LOGIN_
ON_
WEB
:
= 7
NETWORK_
UNAVAILABLE
NETWORK_
UNAVAILABLE
:
= 1
SERVER_
INVALID
SERVER_
INVALID
:
= 8
Sign
Up
Sign
Up
:
= 12
TOKEN_
INCORRECT
TOKEN_
INCORRECT
:
= 31004
UNKNOWN
UNKNOWN
:
= -1
Unconnected
Unconnected
:
= 11
VALIDATE_
INVALID
VALIDATE_
INVALID
:
= 9
WIFI
WIFI
:
= 5
Exports
Connection
StatusIOS
AIRPLANE_
MODE
Cellular_
2G
Cellular_
3
G_
4G
Connected
Connecting
DISCONN_
EXCEPTION
KICKED_
OFFLINE_
BY_
OTHER_
CLIENT
LOGIN_
ON_
WEB
NETWORK_
UNAVAILABLE
SERVER_
INVALID
Sign
Up
TOKEN_
INCORRECT
UNKNOWN
Unconnected
VALIDATE_
INVALID
WIFI
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Ewon Flexy tag information library created by the HMS Networks MU Americas Solution Center.
This library is dependent on the HMS Networks MU Americas Solution Center library for strings,
found at https://www.github.com/hms-networks/sc-string-lib.
This library is dependent on the HMS Networks MU Americas Solution Center library for file
utilities, found at https://github.com/hms-networks/sc-flexy-file-util-lib.
This library is dependent on the HMS Networks MU Americas Solution Center library for JSON
management, found at https://github.com/hms-networks/sc-flexy-json-lib.
@version 1.2.1
@author HMS Networks, MU Americas Solution Center


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